Principles of artificial intelligence
Principles of artificial intelligence
Engineering and compiling planning domain models to promote validity and efficiency
Artificial Intelligence
Remote Agent: to boldly go where no AI system has gone before
Artificial Intelligence - Special issue: artificial intelligence 40 years later
Advanced Planning Technology: Technological Achievements of the ARPA/Rome Laboratory Planning Inititive
The automatic inference of state invariants in TIM
Journal of Artificial Intelligence Research
A Tool Supported Structured Method for Planning Domain Acquisition
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Reading PDDL, writing an object-oriented model
IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
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Recent successful applications of AI planning technology have highlighted the knowledge engineering of planning domain models as an important research area. We describe an implemented translation algorithm between two languages used in planning representation: PDDL, a language used for communication of example domains between research groups, and OCLh, a language developed specifically for planning domain modelling. The algorithm is being used as part of OCLh's tool support to import models expressed in PDDL to OCLh's environment. Here we outline the translation algorithm, and discuss the issues that it uncovers. Although the tool performs reasonably well when its output is measured against hand-crafted OCLh, it results in only partially specified models. Analyis of the translation results shows that this is because many natural assumptions about domains are not captured in the PDDL encodings.